Are 21st-century citizens grieving for their loss of privacy?

Although much research exists that examines cognitive events leading up to information disclosure, such as risk-benefit analysis and state-based and trait-based attributes, minimal research exists that examines user responses after a direct or indirect breach of privacy. The present study examines 1,004 consumer responses to two different high-profile privacy breaches using sentiment analysis. Our findings indicate that individuals who experience an actual or surrogate privacy breach exhibit similar emotional responses, and that the pattern of responses resembles well-known reactions to other losses. Specifically, we present evidence that users contemplating evidence of a privacy invasion experience and communicate very similar responses as individuals who have lost loved ones, gone through a divorce or who face impending death because of a terminal illness. These responses parallel behavior associated with the Kübler-Ross’s five stages of grief

Visually grounded learning of keyword prediction from untranscribed speech

During language acquisition, infants have the benefit of visual cues to ground spoken language. Robots similarly have access to audio and visual sensors. Recent work has shown that images and spoken captions can be mapped into a meaningful common space, allowing images to be retrieved using speech and vice versa. In this setting of images paired with untranscribed spoken captions, we consider whether computer vision systems can be used to obtain textual labels for the speech. Concretely, we use an image-to-words multi-label visual classifier to tag images with soft textual labels, and then train a neural network to map from the speech to these soft targets. We show that the resulting speech system is able to predict which words occur in an utterance---acting as a spoken bag-of-words classifier---without seeing any parallel speech and text. We find that the model often confuses semantically related words, e.g. "man" and "person", making it even more effective as a semantic keyword spotter.Comment: 5 pages, 3 figures, 5 tables; small updates, added link to code; accepted to Interspeech 201

Body Size of the Endosymbiotic Pea Crab Tumidotheres maculatus: Larger Hosts Hold Larger Crabs

The endosymbiotic pea crab, Tumidotheres maculatus, uses a broad range of host taxa, including several bivalve species, in the northern Gulf of Mexico. Because shelter size affects the size of other, free-living crab species, we hypothesized that pea crabs living in larger bivalve hosts should attain larger sizes. Crabs and hosts collected from 3 field sites in northern Florida show this trend. We examined crabs living in a large host, the pen shell Atrina rigida, and found them to be larger than pea crabs living in a small host, the bay scallop Argopecten irradians. Moreover, this trend was only apparent among female pea crabs, which are lifelong endosymbionts, but not among males, which are free-ranging and move among hosts. Our data support the broader conclusion that shelter size influences adult crab size in brachyuran crabs

Anger in academic Twitter:Sharing, caring, and getting mad online

This article examines two different cases or “events” in Twitter to understand the role that negative emotions play in online discussions of academic labor. As academic labor conditions deteriorate and academics take to online spaces, they do so to critique, connect, and organize. We suggest that negative emotions may play a productive role in raising awareness of labor issues, as well as serving as a site for organizing across academic hierarchies and beyond the university. Additionally, negative emotions may fuel the production of new networks, personal, and professional connections. However, as we show, anger online can also provoke substantive repercussions, both personally and institutionally. We suggest that paying attention to the role that negative emotions play on Twitter can help academics gain a better sense of how to use their digital labor for collective action

Digital worker inquiry and the critical potential of participatory worker data science for on‐demand platform workers

The knowledge that workers have of the systems they work under is an outcome of strategic choices by platforms and by workers themselves. Based on three initiatives undertaken by food distribution workers in Scotland, this article explores the obstacles that platform workers face when conducting inquiries into their systems of control, and investigates the potential for workers to overcome these obstacles through collaborative research projects. By drawing analogies from the history of workers' inquiries into changing labour processes, the article evaluates these three initiatives in light of previous efforts by workers to monitor complex and concealed management structures. It offers a new concept of ‘worker data science’ to describe the techniques, skills and methods that workers require to arrive at answers to questions that emerge through their inquiries, and concludes that such purposive science has the potential to equip workers to support one another and to resist and challenge some of the commands and calculations that emerge from platforms' hidden algorithmic systems.Publisher PDFPeer reviewe